The servicing of streaming media requires an expenditure of both storage and computing resources. The limitations that are inherent in these resources assure that bottlenecks in the servicing process will not be relieved unless these limitations are mediated by an appropriate allocation of system resources. The limitations of system resources are exacerbated by inefficiencies that result from the misallocation of system resources. The bottlenecks that are facilitated by these inefficiencies can serve to help overload the computing and storage resources of the streaming media service system and degrade its overall performance.
Conventional systems do not overcome the above noted service process bottleneck problem. In fact, many conventional systems concentrate on the caching of fully serviced data that is taken from an output of the servicing system which can exacerbate the problem. As is readily apparent the caching of such fully serviced data places a severe load on storage resources. This is because such methodologies expend an excessive amount of the systems storage resources so that the expenditure of computing resources necessary to provide future services may be reduced. However, bottlenecks that arise from the lack of storage availability stemming from such misallocations of the storage resources are prevalent.
A major disadvantage of conventional systems that provide data service and delivery is that the tension on one type of system resource is excessively stretched at the same time that there exist an over abundance of another type of system resource. The inefficiencies that result from such media servicing misallocations facilitate the bottlenecks that degrade system performance.